Department of Automatic Control and Systems EngineeringUniversity of Sheffield

ACS(6)340 BiomechatronicsLecture 1 Introduction to Biomechatronics

Dr Sean Anderson

s.anderson@sheffield.ac.uk

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Lecture aims

1. Define the course structure, including:

-Learning Objectives

-Learning Activities

-Assessment and Feedback

2. Introduce and motivate the topic of biomechatronics.

3. Set course work assignment 1.

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Course outline

Part 1

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What is Biomechatronics?

(i) emulate and replace natural human function lost through disease or accident and/or

(ii) augment natural human function to generate superhuman abilities.

‘Biomechatronics’ describes the integration of the human body with engineered, mechatronic devices, to:

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Course learning objectives

1. Explain and summarise the motivation, ethical issues and future challenges in biomechatronics;

2. Analyse, evaluate and compare the design and construction of biomechatronic technologies;

3. Select and apply appropriate dynamic models and computational tools to simulate and analyse biomechatronic systems;

4. Design and construct simple biomechatronic systems using appropriate hardware and instrumentation;

5. Produce a technical report incorporating details of biomechatronic design, methods and experimental results to a standard that a suitably qualified person could follow and use to obtain similar findings.

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Course overviewWeek Topic Learning Activity Assessment

Week 1 Introduction to Biomechatronics 1 lecture (no lab)

Week 2 Neural Control 1 lecture (no lab)

Week 3 Biomedical Signals 1 lecture, 1 lab

Week 4 Sensors, Power, Control 1 lecture, 1 lab

Week 5 Actuators 1 lecture, 1 lab Assignment 1 due

Week 6 Individual Project 1 lecture, 1 lab

Week 7 Individual Project Lab drop-in session

Week 8 Individual Project Lab drop-in session

Week 9 Individual Project Lab drop-in session

Week 10 Problem Class + Project Lecture + Lab drop-in

Week 11 Revision - Exam preparation No lecture Assignment 2 due

Week 12 Revision - Exam preparation No lecture

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Laboratories

• Labs are on Mondays, 9-11am, in the Diamond, DIA-201, i.e. Computer Room 1 (should take ~1.5 hrs)

• No lab in weeks 1 or 2.1. Lab 1 (week 3): Neural control

– Intro to Simulink plus modelling/simulation of a neuromuscular model for prosthetic limb control

2. Lab 2 (week 4): Biomedical signals – Signal processing of EMG plus EMG->force modelling

3. Lab 3 (week 5): Sensors, Power, Control– Human movement observation using inertial meas. unit.

4. Lab 4 (week 6): Actuators– Motors and gearing

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Learning material

1. Printed module handbook, including notes.

2. On MOLE:-Electronic copies of lecture powerpoint slides.-Laboratory briefings.-An example exam paper with solutions.

3. The recommended module textbook is: Brooker, G., (2012). Introduction to Biomechatronics, SciTech Publishing

This book is provided by the library for free in a complete, electronic format as a PDF file from the IET ebooks catalogue.

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Assessment

• Coursework– Assignment 1 (15%): Written summaries of specified

research articles across topics in biomechatronics. (Learning outcomes 1, 2, 5).

– Assignment 2 (35%): Individual technical report based on an individual project into some aspect of biomechatronics to include design and/or computational analysis and/or construction of a simple biomechatronic device. (Learning outcomes 1-5).

• Exam– One 1.5 hour written examination (50%). The exam will

assess learning outcomes 1-4.

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Feedback

Feedback will be given in the following forms:

• Interactively during lab sessions.

• Written, individual feedback on assignments.

• A brief oral summary to the group on assignment 1 during the relevant lecture.

• A brief group summary on assignment 2 by email at the end of semester.

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Overview of Biomechatronics

Part 2

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Learning objectives

• Explain the motivation for biomechatronics, including healthcare challenges and associated biomechatronic treatments.

• Explain the main components of a biomechatronic system.

• Explain the future challenges in biomechatronic system design.

• Explain the ethical issues associated with biomechatronic systems.

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Motivation for biomechatronics

“There are no disabled people, only disabled technologies.”

http://www.tedmed.com/talks/show?id=7035

Prof. H. Herr (MIT)

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Healthcare challenges

In the 21st Century a number of healthcare challenges will be addressed through biomechatronic technology.

Healthcare challenge Technology

Aging population, paralysis, stroke Exoskeletons

Loss of limbs Limb prosthetics

Sight loss Bionic eye

Hearing loss Cochlear implants

Heart Disease Pacemaker

Disease such as Parkinson’s, Epilepsy Implanted electrodes

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Assisted mobility

EKSO Bionics

Exoskeletons can aid movement forpeople who have restricted mobility.

Age, Stroke, Paralysis

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Active prosthetics limbs

• Active prosthetic limbs are typically designed to emulate human movement, for– Energy efficiency– Range of activities– Safety– Comfort– Natural look

• Biomimetic design goals:– Size and mass– Torque and speed

http://www.youtube.com/watch?v=3lkv7iLyiug

Comparison of standard and advanced lower limb prosthetic

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Bionic eye

• Generating neural activity that approximates activity in the intact visual pathway is the overarching goal of visual prosthetics.

In age-related macular degeneration (AMD) and retinitis pigmentosa (RP) photoreceptors degrade.

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Cochlear implants

1. Sound: Information, Noise.

6. Auditory nerve to brain.

2. Signal acquisition (Mic)3. Pre-processing (user control)

4. Signal analysis and processing (clinician control)

5. Electrical/acoustic stimulation

Van Himbeeck, C. (2009). Implantable hearing solutions and the quest for the bionic (wo)man. IET Seminar on Bionic Health: Next Generation Implants, Prosthetics and Devices.

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Components of a Biomechatronic System

Part 3

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The biomechatronic system

• The human subject adds the bio to the mechatronic control and monitoring process.

• The human element is not only the most complex and least understood but also the most difficult to interface to.

Brooker, G. (2012). Introduction to Biomechatronics. SciTech Publishing: Rayleigh, NC.

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Neural control

TU Delft, 2006, Biomechatronics.

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Biomedical signals

• Biomechatronic devices will often use physiological signals observed in real-time from the human subject.

Rothschild, R. M. (2010). Neuroengineeringtools/applications for bidirectional interfaces, brain–computer interfaces, and neuroprostheticimplants–a review of recent progress. Frontiers in neuroengineering, 3(112), 1-15.

E.g. muscle activity (EMG) and neural/brain activity (EEG).

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Sensors, Power and Control• Biomechatronic systems are

designed/constructed using tools we are already familiar with…

• E.g. sensors, control loops, transfer functions, dynamic models

Eilenberg, M. F., Geyer, H., & Herr, H. (2010). Control of a powered ankle–foot prosthesis based on a neuromuscular model. IEEE Trans. Neural Systems and Rehabilitation Engineering, 18(2), 164-173.

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Actuators

Standard Actuators• Motors, hydraulics, pneumatics

Future actuators• Shape memory alloys,

electroactive polymers

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Example: EMG control of prosthetic hand

Time

EMG Signal

Open hand

Closed hand Automated Movement Classification and Control

8 channel EMG Sensing and Signal Processing

Fig below: 8 channel EMG control of prosthetic hand

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Future Challenges and Ethical Issues

Part 4

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Future challenges: overview

• Electromechanical design.

• Estimation of ‘user-intention’.

• User acceptance.

Kazerooni, H. (2005, August). Exoskeletons for human power augmentation. In IEEE/RSJ International Conference on Intelligent Robots and Systems,

2005.(IROS 2005). (pp. 3459-3464).

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Future challenges: sensory feedback

Motor Command Decoding

• Biomechatronicdevices are already very sophisticated.

• However, these devices tend to lack full integration with the body – e.g. sensory feedback for closed loop control.

Raspopovic, S., Capogrosso, M., Petrini, F. M., Bonizzato, M., Rigosa, J., Di Pino, G., ... & Micera, S. (2014). Restoring natural sensory feedback in real-time bidirectional hand prostheses. Science translational medicine, 6(222), 222ra19-222ra19.

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Ethics in biomechatronics

Attiah MA and Farah MJ (2014). Minds, motherboards and money: futurism and realism in the neuroethics of BCI technologies, Frontiers in Systems Neuroscience, Vol. 8, 1-3.

-Ownership of intellectual property (IP)-Benefit versus profit-Influence of funding sources

-Cost of BCIs as an obstacle-Discomfort/disgust with augmentation-Security against hacking

-Cyborg treatment of humans-Loss of individuality (group mind)-Immortality of mind

Short term:Use in research

Medium term:Use in Therapy

Long term:Extensive Enhancement

Ethical timeline

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Assignment 1

Part 5

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Assignment 1 Task

The task is to read and summarise four research articles, detailed in the lists below. Each summary should be about 200 words.Mandatory list. You must include these two papers in your summaries:

• Dellon B and Matsuoka Y (2007). Prosthetics, Exoskeletons and Rehabilition. IEEE Robotics and Automation Magazine, Vol. 14, 30-34.

• Attiah MA and Farah MJ (2014). Minds, motherboards and money: futurism and realism in the neuroethics of BCI technologies. Frontiers in Systems Neuroscience, Vol. 8, 1-3.

Optional list. You must include two papers (only) from this optional list:• Gopura R, Kiguchi K and Bandara D (2011). A brief review on upper extremity robotic

exoskeleton systems. Proceedings of the 6th International Conference on Industrial and Information Systems, 346-351.

• Haddad, S. A., Houben, R. P., & Serdijin, W. A. (2006). The evolution of pacemakers. IEEE Engineering in Medicine and Biology Magazine, 25 (3), 38-48.

• Loizou, P. C. (1999). Introduction to cochlear implants. IEEE Engineering in Medicine and Biology Magazine, 18(1), 32-42.

• Lovell NH, Morley JW, Chen, SC, Hallum LE and Suaning GJ (2010). Biological-Machine Systems Integration: Engineering the Neural Interface. Proceedings of the IEEE, Vol. 98, 418-431.

• Martin J, Pollock A, Hettinger J (2010). Microprocessor Lower Limb Prosthetics: Review of Current State of the Art. JPO: Journal of Prosthetics and Orthotics, Vol. 22, 183-193.

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Assignment 1 Details

• Submission date: Monday of week 5

• Submit via the Turnitin link on MOLE

• Find the papers via Google scholar, https://scholar.google.co.uk/

• Feedback: will be individual, written, on MOLE, within two weeks of the submission date.